Urinary Metabolite Profile Predicting the Progression of CKD

Abstract

Background: Since chronic kidney disease (CKD) is caused by genetic and environmental factors, biomarker development through metabolomic analysis, which reflects gene-derived downstream effects and host adaptation to the environment, is warranted. Methods: We measured the metabolites in urine samples collected from 789 patients at the time of kidney biopsy and from urine samples from 147 healthy subjects using nuclear magnetic resonance (NMR). The composite outcome was defined as a 30% decline in estimated glomerular filtration rate (eGFR), doubling of serum creatinine levels, or end-stage kidney disease. Results: Among the 28 candidate metabolites, we identified 7 metabolites showing 1) good discrimination between healthy controls and patients with stage 1 CKD and 2) a consistent change in pattern from controls to patients with advanced-stage CKD. Among the 7 metabolites, betaine, choline, glucose, fumarate, and citrate showed significant associations with the composite outcome after adjustment for age, sex, eGFR, the urine protein-creatinine ratio, and diabetes. Furthermore, adding choline, glucose, or fumarate to traditional biomarkers, including eGFR and proteinuria, significantly improved the ability of the net reclassification improvement (P<0.05) and integrated discrimination improvement (P<0.05) to predict the composite outcome. Conclusion: Urinary metabolites, including betaine, choline, fumarate, citrate, and glucose, were found to be significant predictors of the progression of CKD. As a signature of kidney injury-related metabolites, it would be warranted to monitor to predict the renal outcome.

CKD Urine Metabolomics: Modern Concepts and Approaches

“…Furthermore, resolution and sensitivity enhancement could be achieved by different MS instrumentation. The prevalent amount of CKD metabolomic works were made using time-of-flight mass spectrometry (TOF-MS) [ 23 , 36 , 39 , 42 ] and quadrupole time-of-flight mass spectrometry (Q-TOF-MS) [ 43 , 44 , 45 , 46 ], which is characterized by high sensitivity, fast scanning speeds, and accurate mass measurements. However, in one of the works, both Q-TOF-MS and reconstitution techniques were performed [ 40 ].…”

“…We can hypothesize that the association between indoxyl sulfate and the microbiome in CKD may combine with TMAO to form markers of a common underlying cause. The association of metabolites with the microbiome is potentially problematic for early-stage CKD diagnosis [ 45 ]. However, such an assertion should be supported by evidence.…”